<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->
legal_text_classifier_Text10
This model is a fine-tuned version of aubmindlab/bert-base-arabertv2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.9829
- F1: 0.6587
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
Training Loss | Epoch | Step | Validation Loss | F1 |
---|---|---|---|---|
No log | 1.0 | 188 | 1.4532 | 0.6138 |
No log | 2.0 | 376 | 1.1460 | 0.6018 |
1.4397 | 3.0 | 564 | 0.9773 | 0.6737 |
1.4397 | 4.0 | 752 | 0.9158 | 0.6886 |
1.4397 | 5.0 | 940 | 0.9531 | 0.6677 |
0.6757 | 6.0 | 1128 | 0.9563 | 0.6707 |
0.6757 | 7.0 | 1316 | 0.9572 | 0.6587 |
0.496 | 8.0 | 1504 | 0.9772 | 0.6497 |
0.496 | 9.0 | 1692 | 0.9840 | 0.6617 |
0.496 | 10.0 | 1880 | 0.9829 | 0.6587 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1